43 Paid Search Signals You Need To Understand

The SEO world often talks about the idea of signals – data points used by search engines to deliver the most relevant results. But the paid search community almost never discusses them (a point Kevin Lee made two years ago). Yet, our ability to participate and profit from ad auctions is dependent on a deep understanding and manipulation of a wide variety of signals.
Google is a publisher. Their systems are designed to maximize the yield on their search results – to maximize the number of searches, clicks on paid search ads per search, and the cost of those clicks.
As advertisers, our goal is to maximize the yield on our media spend – to maximize the number of clicks, conversions per clicks, profit per click, and minimize the cost per click.
Both parties incorporate at least 43 signals that answer six fundamental questions to value and satisfy the search and searcher:

• What are they searching for?
• How much is the search worth?
• Who is searching?
• How are they searching?
• When are they searching?
• Where are they searching?

What Are They Searching For?

Intent is far and away the most important tool for maximizing profit. What someone says they want right now is the core signal to determine the right combination of ads to display, if any.

• Search Query – The raw words someone types (as opposed to the keywords you bid on) are the most direct and literal expression of a searcher’s goals. The fact that they’re searching for it at this instant often indicates a higher degree of commercial intent and likelihood to convert.  
• Relevance – This is the vaguest of the signals, which Google defines as “the usefulness of information to a user (such as an ad, keyword, or landing page).” Mostly, it’s what ads have been clicked on most frequently in the past for those searches.  Many times, a search query can have ambiguous intent (does “Paris hotels” refer to Paris, France or Paris, Texas?) and Google relies on other data to determine the right ads for the SERP.

How Much Is The Search Worth?

Google only gets paid when people click on ads. As a result, advertising on Google isn’t a direct auction where the highest bidder automatically gets the top spot, because there’s no guarantee that the person with the most money has the most compelling ad.
Instead, Google looks at a combination of quality fit and economic fit. Put another way, they calculate ad rank by multiplying your bid times quality score.

Quality Fit 

The best quality fit for Google, in most cases, is ad most likely to be clicked on. Google has disclosed some of the components of quality fit, most thoroughly documented in "Quality Score in High Resolution."
In general, more data is better and newer data is better. The greater your reputation for getting searchers to click on your ads – historical, recent and specific to the current search and searcher – the more likely you are to have your ads displayed in the auction in a higher position at a more favorable price.

• Keyword/Text Ad Pair: Not surprisingly, the performance of a given text ad for a given keyword weighs most heavily. It’s the closest scenario to mimicking someone’s current search and likely response to your ad. 
• Display URL – People like to know where they’re going after they click. The display URL, the one people see in your ad vs. the coded URL you link to, has a quality measure all its own.
• Account – The sum total of your past performance creates an account wide reputation that affects each auction.
• Landing Page Assessment – Google had s specific landing page quality score that either applies a penalty to your account or is neutral. Essentially, if your business model is poor or your site experience horrendous, Google believes this will negatively impact people’s likelihood to trust and click on ads and you are penalized accordingly.
• Ad Extensions – Google offers a wide variety of ad extensions to append additional information, pictures and calls to action to your text ad. Google has said explicitly that one format, sitelinks, don't impact quality score. However, they will factor in past clickthrough rate (CTR) performance when determining which links to display. 
• Similar Performance – In the absence of specific data for this keyword with this advertiser, Google will look at the performance of keyword from other advertisers on the same keyword. Google’s AdWords Evangelist Frederick Vallaeys illustrate this concept with the example of the actress Jessica Alba. Many advertisers have tried to capitalize on her fame by advertising a wide variety of goods on her name. Most searchers, however, are only looking for information about the actress. As a result, most advertisers using “Jessica Alba” as a keyword would receive a very low initial quality Scsre.

Economic Fit

No matter how great your great quality score, there is a minimum amount you have to pay to get on the first page and, based on a competition, an increasing amount you have to pay to move up the page.

• Bid - Bids only play an indirect role in determining CPC, but a direct relationship in determining ad rank. The amount you’re willing to pay for a click actually takes several forms, depending upon the network, product and extension you’re using.
• Regular bids – Standard bids on both the search and display network
• Cost-per-Acquisition (CPA) – Certain ad formats, such as Product Listing Ads and Comparison Ads, are sold to a select group of advertisers on a CPA basis. 
• Enhanced CPC – AdWords can automatically adjust your Max CPC up to 30 percent if you’ve enabled this option. It uses historical AdWords conversion tracking data to determine if a click is more likely to convert.
• Conversion Optimizer – The AdWords integrated bid management tool allows users to set a target CPA instead of CPC bidding. For the purposes of the auction, it’s likely Google then estimates conversion rate and translate this into a maximum bid, but that process is opaque. 
• Flat Fee Pricing – Some ad formats, like Media Ads, charge a flat amount for certain interactions, in this case clicks to play a video trailer. That’s also true for extensions such as locations which may result in clicks for directions. At this point, it appears these pricing models don’t affect your ability to appear in auctions or your ad rank.

• Conversion and Profitability – For most auctions, all of Google’s signals rely entirely on economic data related to their profit (CPCs, CTR) not our profit as advertisers, save for the exceptions noted above.

We obviously use different and more varied signals to value search traffic, including:

• Conversions – The raw number of sales or leads, regardless of differences in value
• Conversion Rate – The percentage of clicks that turned into sales or leads
• Average Order Value – The average total amount purchased 
• CPA – The cost per acquisition (a.k.a., conversion, lead, or sale)
• Return on ad spend (ROAS) – Revenue over cost, which may or may not equate to a positive profit, depending upon your margins.
• Return on Investment (ROI) – Return, subtracting advertising and variable cost of goods sold.
• Lead Quality Metrics – For lead gen companies, such as B2B marketers, there are signals of lead quality, like lead score and opportunities created, that help establish proxies for quality before a lead closes after a long sales cycle.
• Lifetime Value (LTV) – Some customers are worth more than others for subsequent purchases, for example discount purchasers vs. full price purchasers. 

Who Is Searching?

Not every searcher is equally likely to click on a specific set of ads, even if they’re using the same terms. And on the Display Network, where no search query can indicate intent, more signals are necessary to deliver the most relevant ad.
Google has a variety of data to determine not just what you want, but who you are (in an anonymous way, of course). This pulls from behavioral data gathered from AdSense and remarketing cookies, social connections from Google and other online profiles, topical interests gathered from sites visited in the Display Network and even demographic information from third parties.

Behavior

Search queries are the greatest indicator of intent, because they are explicit and recent. In addition to, or in the absence of, search queries, recent and historical browsing behavior can help us and Google to value and target different audiences appropriately.

• Remarketing (retargeting) cookies – Cookies can be set, via a small snippet of JavaScript code, on any section of your site to segment users. These cookies create groups, which can be mixed and matched, to allow specific ad serving on the display network. For example, advertising free shipping to visitors who added items to a cart, but who did not check out. 
• Interests – Using anonymous browsing data across the Display Network, Google builds profiles of users based on their likely affinity to specific topics. For example, people who visit a lot of golf related pages or sites for expectant mothers. 

Social

Last week, Google rolled out their +1 button that allows users to share pages with their network of contacts in both paid and organic results. For more detail on social signals and PPC, read my previous column, "How Social Media Affects Paid Search ."

• Relationships – In addition to seeing general counts of +1s, you’ll also see images for direct connections that have +1ed something in the search results. These +1s won’t directly impact your quality score (and thus, ad rank). They will, however, indirectly impact quality score through their influence on CTR. 
• Your +1s – Search results will include your own +1s in the results, reinforcing your own affinities. 

Interests

Display network targeting works either through managed placements, where we choose specific sites, or automatic placements, where Google analyzes the keywords in the ad group to pair with thematically similar sites and pages. There is also middle ground for targeting called topics.

• Topics – Groups of related sites built around one specific topic, for example home improvement. These are similar to ad networks that group together independent sites of similar content for ease and scale of targeting. The idea is that there are similar audiences, both in terms of interest and composition. 

Demographics

Some sites on the Google Display Network, such as social networking sites, collect and opt to share demographic data. Google, which it’s worth noting does not collect these data themselves, enables specific bidding on demographic data when available.
Similar to enhanced CPC, bids are adjusted in real time when the data are available and the preferred audience is available, including:

• Age
• Gender
• Household education
• Household income

How Are They Searching?

The way people search, especially the device they use, and where the network where the ads are served, search vs. search partners vs. display, can say a lot about what someone is looking for.
Mobile devices are probably the most dramatic example of this. If you’re searching for car rental from your phone at Heathrow, it’s pretty safe bet you want a rental company in London and need a car right now.
How you search provides implicit signals of relevance.

Device

Mobile searches are different. Users are very local. For example, 53 percent of mobile searches on Bing have a local intent. Eric Schmidt from Google also said “1 in 3 queries from smartphones is about where I am.”
Mobile users are also very urgent. Seventy percent of PC “query chains” (essentially search tasks) are completed in about one week while 70 percent of mobile users do so in one hour.
Similarly, Pew Research found that:

Around one in ten Americans with annual household incomes of $75,000 or more own a tablet PC or e-book reader, while fewer than 5% of households earning less than $50,000 per year contain one of these devices.

Not surprisingly, the different sized screens, download speeds, and mindset of searchers among the devices means that maximizing yield requires different ad types and, sometimes, advertisers.

• Desktop/laptop – People who aren’t searching on the go.
• Phone – Ads served only to phones, regardless of browser type.
• Smartphone – Mobile devices with full Internet browsers.
• Tablet – You can target tablets with full browsers, which covers iPad, Android, Playbooks and others.
• Operating System – Google is rolling out targeting to specific operation systems, such as iOS and Android
• Carrier – Specific phone plan providers, which vary by region.

Network

By default, Google lumps together campaigns to target both the search network, people who are actively searching on Google.com or one of their search partners, and the Display Network, the sites that monetize with AdSense.
This is a clear money grab, because the way you manage search and display network campaigns is entirely different, requiring different ad group structures, creative, and bids.

• Search – Ads triggered based on search queries, primarily on Google.
• Search Partners – Sites with search results powered by Google. You can’t target them explicitly, but you can opt out of them in any campaign.
• Display Network – The group of sites running AdSense has almost nothing to do with search. It’s a push medium where you are interrupting the user’s main activity (interacting with content) vs. a pull medium where you’re satisfying their central need (searching). The ad formats, targeting methods, CPCs and so on are dramatically different. Similarly, optimizing the yield for display ads is different, factoring in more audience and behavioral data.

When Are They Searching?

Temporal signals, the time when someone searches, can hint at your needs or value: weekends vs. weekdays, days vs. nights, work vs. home, and so on.

• Dayparting – Queries can have a different meaning or value depending on the time of day.
• Weekparting – Response can vary by day of the week or a business could restrict ads to days of operation. 

Where Are They Searching?

Not every searcher is equally likely to click on a specific set of ads, even if they’re using the same terms. Take the previous example of “paris hotels.” The auction for someone searching with that query in Texas would look very different than someone in France.
This is especially true for local searches, such as “Philadelphia gym,” which can often trigger results from local specific ad formats, such as location extensions and Google Boost.

Physical

• Physical Location – Google will look at a searchers IP location and the Google top level domain (google.com vs. google.co.uk, for example) to determine where they’re searching from. 
• Search Intent – Sometimes a search query includes a geo-modifier, such as “Philadelphia byob,” indicating a person is either in the desired in the geographic region even if their IP doesn’t specify as much or is simply interested in local business. Read more.

Not All Signals Matter Equally

Groups are not homogenous. Groups don’t purchase or click on ads, people do. Every signal is used at a tool to determine which specific set of ads are most likely to appeal to this particular person at this particular time.
Intent gathered from a search query is the clearest window into what someone wants and when, because it is both explicit and immediate.
Behavioral data, especially that used for remarketing, is also very influential, because of the ability to target people based on recency of behavior (varying the cookie length) and value of the action (by creating small segments using multiple tags).
The greater of a predictor of someone’s likelihood to click, the greater the weight that signal carries. The less explicit, recent and specific the signal, the less influence it has. I hypothesize the priority looks like this:

What Do Signals Mean to Advertisers?

Google prioritizes what drives their bottom line (CPCs, clicks). We need to understand what they care about and manage accordingly, for example improving CTR to boost quality score.
Ultimately, however, we need to prioritize what drives ours (profit, leads). The more accurately we can value a click, the better we can extract profit from it.

Whoever Has The Data Wins

If there’s one thing that should be clear from this article, it’s that data drives results. Newer data is better than older data. More data is better than less data.
Google clearly understands that whoever has the data wins.
This is doubly true for advertisers, because we know what happens after the click. We can optimize landing pages, offers, checkout, and other conversion variables. We can also determine which kinds of customers are most profitable in the short term and over time (LTV).
Like Google, we must compete with data to maximize our yield. As auctions become more competitive and new ad formats remove some of the typical controls, such as is the case with product listing ads, which don't require keywords, the ability to successfully target, value, and convert niche audiences will separate the most profitable companies from the least.
Put more simply, we need data to move budget from early funnel to late funnel targeting.

Technology is a Necessity, Not a Luxury

Operating at scale can't be done manually. Google doesn't have a sales team negotiating each search result, even for the highest volume, most valuable terms. Automated systems are required to handle data at scale
All advertisers of significant size need their own suite of paid search tools to automate the use of signal data to the degree possible. They reduce human error, operate at a higher speed and breadth, and free up talent to focus on strategy instead of tactics.

A Caveat

This list is not exhaustive. It couldn’t possibly be. Like organic search rankings, there are surely more signals that Google uses to manage the auctions that are not published. Not every tool Google uses to maximize yield is available to advertisers. Likewise, not every signal we use to maximize our yield factors into the auction.
It’s also important to remember that, like SEO, not every signal carries equal weight. If you’re dayparting campaigns with big, unrelated ad groups, poorly written text ads and sub-optimal landing pages, then you’re just rearranging flatware on the Titanic.
My hope is that this article will establish signals as part of the PPC managers’ vocabulary, so that we can continue to document and prioritize them for everyone’s benefit and to inspire Google to offer more transparency. If you can think of any signals I missed, or want to take a stab at prioritizing them, please leave a comment.

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